Human Trust
Human trust, particularly in the context of human-AI interaction, is a multifaceted research area focusing on understanding how trust develops, is maintained, and can be influenced. Current research emphasizes both cognitive and emotional aspects of trust, employing models like Bayesian relational event modeling and inverse reinforcement learning to analyze and predict trust dynamics in various scenarios, including human-robot collaboration and AI-assisted decision-making. These investigations are crucial for developing trustworthy AI systems and improving human-AI collaboration across diverse applications, from cyber defense to shared autonomy in robotics.
Papers
Trust-Aware Assistance Seeking in Human-Supervised Autonomy
Dong Hae Mangalindan, Ericka Rovira, Vaibhav Srivastava
Enhancing Community Vision Screening -- AI Driven Retinal Photography for Early Disease Detection and Patient Trust
Xiaofeng Lei, Yih-Chung Tham, Jocelyn Hui Lin Goh, Yangqin Feng, Yang Bai, Zhi Da Soh, Rick Siow Mong Goh, Xinxing Xu, Yong Liu, Ching-Yu Cheng